Vehicle defect discovery from social media

Vehicle defect discovery from social media

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Article ID: iaor20127331
Volume: 54
Issue: 1
Start Page Number: 87
End Page Number: 97
Publication Date: Dec 2012
Journal: Decision Support Systems
Authors: , , ,
Keywords: quality & reliability
Abstract:

A pressing need of vehicle quality management professionals is decision support for the vehicle defect discovery and classification process. In this paper, we employ text mining on a popular social medium used by vehicle enthusiasts: online discussion forums. We find that sentiment analysis, a conventional technique for consumer complaint detection, is insufficient for finding, categorizing, and prioritizing vehicle defects discussed in online forums, and we describe and evaluate a new process and decision support system for automotive defect identification and prioritization. Our findings provide managerial insights into how social media analytics can improve automotive quality management.

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